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/*
* Copyright (c) 2023 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef ACL_TESTS_DATASETS_REORDERLAYERDATASET
#define ACL_TESTS_DATASETS_REORDERLAYERDATASET
#include "arm_compute/core/TensorShape.h"
#include "arm_compute/core/Types.h"
#include "utils/TypePrinter.h"
namespace arm_compute
{
namespace test
{
namespace datasets
{
/** [ReorderLayer datasets] **/
class ReorderLayerDataset
{
public:
using type = std::tuple<TensorShape, TensorShape, WeightFormat, WeightFormat>;
struct iterator
{
iterator(std::vector<TensorShape>::const_iterator in_it,
std::vector<TensorShape>::const_iterator out_it,
std::vector<WeightFormat>::const_iterator _wf_in_it,
std::vector<WeightFormat>::const_iterator _wf_out_it)
: _in_it{ std::move(in_it) },
_out_it{ std::move(out_it) },
_wf_in_it{ std::move(_wf_in_it) },
_wf_out_it{ std::move(_wf_out_it) }
{
}
std::string description() const
{
std::stringstream description;
description << "In=" << *_in_it << ":";
description << "Out=" << *_out_it << ":";
description << "Wf_In=" << *_wf_in_it << ":";
description << "Wf_Out=" << *_wf_out_it;
return description.str();
}
ReorderLayerDataset::type operator*() const
{
return std::make_tuple(*_in_it, *_out_it, *_wf_in_it, *_wf_out_it);
}
iterator &operator++()
{
++_in_it;
++_out_it;
++_wf_in_it;
++_wf_out_it;
return *this;
}
private:
std::vector<TensorShape>::const_iterator _in_it;
std::vector<TensorShape>::const_iterator _out_it;
std::vector<WeightFormat>::const_iterator _wf_in_it;
std::vector<WeightFormat>::const_iterator _wf_out_it;
};
iterator begin() const
{
return iterator(_in_shapes.begin(), _out_shapes.begin(), _in_wfs.begin(), _out_wfs.begin());
}
int size() const
{
return std::min(_in_shapes.size(), std::min(_out_shapes.size(), std::min(_in_wfs.size(), _out_wfs.size())));
}
void add_config(TensorShape in, TensorShape out, WeightFormat in_wf, WeightFormat out_wf)
{
_in_shapes.emplace_back(std::move(in));
_out_shapes.emplace_back(std::move(out));
_in_wfs.emplace_back(std::move(in_wf));
_out_wfs.emplace_back(std::move(out_wf));
}
// protected:
ReorderLayerDataset() = default;
ReorderLayerDataset(ReorderLayerDataset &&) = default;
private:
std::vector<TensorShape> _in_shapes{};
std::vector<TensorShape> _out_shapes{};
std::vector<WeightFormat> _in_wfs{};
std::vector<WeightFormat> _out_wfs{};
};
/** [ReorderLayer datasets] **/
class ReorderLayerDatasetBlock4 final : public ReorderLayerDataset
{
public:
ReorderLayerDatasetBlock4()
{
add_config(TensorShape(10U, 9U), TensorShape(10U, 12U), WeightFormat::OHWI, WeightFormat::OHWIo4);
add_config(TensorShape(16U, 16U), TensorShape(16U, 16U), WeightFormat::OHWI, WeightFormat::OHWIo4);
add_config(TensorShape(10U, 511U), TensorShape(10U, 512U), WeightFormat::OHWI, WeightFormat::OHWIo4);
add_config(TensorShape(234U, 301U), TensorShape(234U, 304U), WeightFormat::OHWI, WeightFormat::OHWIo4);
add_config(TensorShape(1024U, 1024U), TensorShape(1024U, 1024U), WeightFormat::OHWI, WeightFormat::OHWIo4);
add_config(TensorShape(10U, 9U, 1U, 1U), TensorShape(10U, 12U, 1U, 1U), WeightFormat::OHWI, WeightFormat::OHWIo4);
add_config(TensorShape(16U, 16U, 1U, 1U), TensorShape(16U, 16U, 1U, 1U), WeightFormat::OHWI, WeightFormat::OHWIo4);
add_config(TensorShape(10U, 511U, 1U, 1U), TensorShape(10U, 512U, 1U, 1U), WeightFormat::OHWI, WeightFormat::OHWIo4);
add_config(TensorShape(234U, 301U, 1U, 1U), TensorShape(234U, 304U, 1U, 1U), WeightFormat::OHWI, WeightFormat::OHWIo4);
add_config(TensorShape(1024U, 1024U, 1U, 1U), TensorShape(1024U, 1024U, 1U, 1U), WeightFormat::OHWI, WeightFormat::OHWIo4);
}
};
class ReorderLayerDatasetBlock8 final : public ReorderLayerDataset
{
public:
ReorderLayerDatasetBlock8()
{
add_config(TensorShape(10U, 9U), TensorShape(10U, 16U), WeightFormat::OHWI, WeightFormat::OHWIo8);
add_config(TensorShape(16U, 16U), TensorShape(16U, 16U), WeightFormat::OHWI, WeightFormat::OHWIo8);
add_config(TensorShape(10U, 511U), TensorShape(10U, 512U), WeightFormat::OHWI, WeightFormat::OHWIo8);
add_config(TensorShape(234U, 301U), TensorShape(234U, 304U), WeightFormat::OHWI, WeightFormat::OHWIo8);
add_config(TensorShape(1024U, 1024U), TensorShape(1024U, 1024U), WeightFormat::OHWI, WeightFormat::OHWIo8);
add_config(TensorShape(10U, 9U, 1U, 1U), TensorShape(10U, 16U, 1U, 1U), WeightFormat::OHWI, WeightFormat::OHWIo8);
add_config(TensorShape(16U, 16U, 1U, 1U), TensorShape(16U, 16U, 1U, 1U), WeightFormat::OHWI, WeightFormat::OHWIo8);
add_config(TensorShape(10U, 511U, 1U, 1U), TensorShape(10U, 512U, 1U, 1U), WeightFormat::OHWI, WeightFormat::OHWIo8);
add_config(TensorShape(234U, 301U, 1U, 1U), TensorShape(234U, 304U, 1U, 1U), WeightFormat::OHWI, WeightFormat::OHWIo8);
add_config(TensorShape(1024U, 1024U, 1U, 1U), TensorShape(1024U, 1024U, 1U, 1U), WeightFormat::OHWI, WeightFormat::OHWIo8);
}
};
} // namespace datasets
} // namespace test
} // namespace arm_compute
#endif /* ACL_TESTS_DATASETS_REORDERLAYERDATASET */